A small project to generate double beta decays (with and without neutrinos). Return energies and angles between electrons in the decay.
The following projects are required for successfull compilation:
- GSL (GNU Scientific Library)
- Boost with components:
- python3
- system
- numpy-py3
- PythonLibs
- Python with component NumPy
In order to compile it do:
> cmake
> make
This sohuld produce "lib" folder with libDecayGenerator.so
In order to use the package in Python just add the folder with libDecayGenerator.so to your sys path as :
import sys
import numpy as np
import matplotlib.pyplot as plt
sys.path.append("/path/to/the/decayer/lib/")
from libDecayGenerator import DecayGenerator
dec = DecayGenerator("MM")
dec.setSeed(5789) # Random number seed
max_ev_per_try = 50000 # Due to internal limitations not more than 1e5 events should be generated at once
nevents = 1000000
events = {}
for m in ["2vbb", "MM", "RHC"]:
print("Model : ", m)
events_left = nevents
events[m] = np.zeros((0,3))
dec.setModel(m)
while events_left > 0:
if events_left > max_ev_per_try: cur_nevents = max_ev_per_try
else: cur_nevents = events_left
events[m] = np.concatenate( (events[m],
dec.GenerateEvents(cur_nevents) ))
### The generation function returns 3xN array with values of [T1, T2, costheta]
events_left = events_left - cur_nevents
#### And making a plot
bins = np.linspace(-1.0,1.0,101)
fig = plt.figure(figsize=(12,8), facecolor="w")
hist_MM = np.histogram(events['MM'][:,2], bins=bins)[0]
plt.step(bins, np.append(hist_MM, [0]), where = "post", color="r", label="Mass mixing")
hist_RHC = np.histogram(events['RHC'][:,2], bins=bins)[0]
plt.step(bins, np.append(hist_RHC, [0]), where = "post", color="b", label="RHC")
hist_2vbb = np.histogram(events['2vbb'][:,2], bins=bins)[0]
plt.step(bins, np.append(hist_2vbb, [0]), where = "post", color="g", label="2vbb")
plt.xlim(bins[0], bins[-1])
plt.ylim(0.0,plt.ylim()[1])
plt.legend(ncol=3, fontsize = 18, loc=9,framealpha=1)
plt.xlabel(r"$\cos(\theta_{12})$", fontsize=18)
plt.ylabel(r"Frequency [ a.u. ]", fontsize=18)
plt.show()It should produce a figure similar to this one:
